dipy_track_pft#
Synopsis#
Workflow for Particle Filtering Tracking.
This workflow uses a saved peaks and metrics (PAM) file as input. See [1] for further details about the method.
Usage#
dipy_track_pft [OPTIONS] pam_files wm_files gm_files csf_files seeding_files
Input Parameters#
pam_files
- Path to the peaks and metrics files. This path may contain
wildcards to use multiple masks at once.
wm_files
Path to white matter partial volume estimate for tracking (CMC).
gm_files
Path to grey matter partial volume estimate for tracking (CMC).
csf_files
Path to cerebrospinal fluid partial volume estimate for tracking (CMC).
seeding_files
A binary image showing where we need to seed for tracking.
General Options#
--step_size
Step size (in mm) used for tracking.
--seed_density
- Number of seeds per dimension inside voxel.
For example, seed_density of 2 means 8 regularly distributed points in the voxel. And seed density of 1 means 1 point at the center of the voxel.
--pmf_threshold
Threshold for ODF functions.
--max_angle
Maximum angle between streamline segments (range [0, 90]).
--pft_back
Distance in mm to back track before starting the particle filtering tractography. The total particle filtering tractography distance is equal to back_tracking_dist + front_tracking_dist.
--pft_front
Distance in mm to run the particle filtering tractography after the the back track distance. The total particle filtering tractography distance is equal to back_tracking_dist + front_tracking_dist.
--pft_count
Number of particles to use in the particle filter.
--save_seeds
If true, save the seeds associated to their streamline in the ‘data_per_streamline’ Tractogram dictionary using ‘seeds’ as the key.
--min_wm_pve_before_stopping
Minimum white matter pve (1 - stopping_criterion.include_map - stopping_criterion.exclude_map) to reach before allowing the tractography to stop.
Output Options#
--out_dir
Output directory. (default current directory)
--out_tractogram
Name of the tractogram file to be saved.
References#
Garyfallidis, E., M. Brett, B. Amirbekian, A. Rokem, S. Van Der Walt, M. Descoteaux, and I. Nimmo-Smith. Dipy, a library for the analysis of diffusion MRI data. Frontiers in Neuroinformatics, 1-18, 2014.